Director Overlaps in Mutual Fund Families
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This version: April 4, 2015 Director Overlaps in Mutual Fund Families Abigail S. Hornstein and Elif Sisli Ciamarra* Abstract We examine a unique characteristic of mutual fund governance: a common set of directors serving simultaneously on boards of multiple funds within a fund family (director overlap). At first glance, this governance structure appears to benefit investors because it is associated with higher disclosed mutual fund returns. However, we present evidence that higher disclosed returns are not due to the selection of skilled managers by the board, but due to window dressing and strategic performance transfer from low-fee funds to high-fee funds. In addition, families that have higher board overlap tend to have higher 12b-1 fees, which have been criticized as being the least transparent cost component for mutual fund investors. Such board structures seem to benefit fund families as a whole, rather than the individual funds to which they have fiduciary responsibilities, as families with greater degrees of director overlap enjoy larger asset inflows. Keywords: mutual funds, board of directors, managerial skill, window dressing, performance transfer JEL codes: G23, G11, G34 * Abigail S. Hornstein, Wesleyan University, Middletown, CT, ahornstein@wesleyan.edu; Elif Sisli Ciamarra, Brandeis University, Waltham, MA, esisli@brandeis.edu, corresponding author. We thank Daniel Bergstersser, Kathryn Graddy, Jens Hilscher, Aldo Musacchio, Debarshi Nandy and seminar participants at the Brandeis International Business School and Hunter College. Hornstein thanks the Mellon Foundation for financial support. Part of this work was completed while Hornstein was a visiting scholar at New York University’s Stern School of Business. We also gratefully thank Deniz Civril, Yubing Cui, Eugene Kisselev, Geofrey Lordi, Brian Lau, Alex Moris, Jimmy Ong, Richa Sahay and Na Wang for excellent research assistance. All errors are our own. 1. Introduction The majority of mutual funds in the U.S. are set up by mutual fund sponsors (such as Fidelity, Vanguard, Merrill Lynch), which manage and sell multiple individual funds. When a fund is initially incepted, its board of directors is appointed by the fund sponsor that launches the fund. The board of the newly launched fund is often composed of the same directors that serve the rest of the funds in the fund family. Therefore, a dominant board structure in the U.S. mutual fund families has emerged: a common set of directors serving simultaneously on boards of multiple funds. For example, Fidelity's bond, money market, and asset allocation funds are seen by one board of directors, and another board oversees its equity and high income funds. Fidelity is not an exception in the mutual fund industry. The Investment Company Institute (ICI) reports that the majority of the mutual funds in the U.S. possess a unitary board structure, where a single board governs all of the funds operating under the fun family’s umbrella. The rest of the funds follow a cluster board model, where a few boards oversee multiple funds within the family like in the case of Fidelity (ICI, 2009; ICI, 2012). The main rationale for the prevalence of the overlapping board structure within the mutual fund industry is the presumption that it leads to economies of scale. For example, The Independent Directors Council Task Force Report on Director Oversight of Multiple Funds (May 2005) concludes that “mutual funds within a fund family share the same investment adviser and other key service providers and, as a result, significant efficiencies are realized when a single or limited number of boards oversee all of the funds.” It is also frequently contended that cluster boards that negotiate with fund service providers are able to drive down the funds’ expenses due to the increase in their bargaining power when they negotiate for multiple funds (Kong and Tang, 2007). The economies of scale and bargaining power arguments imply lower costs for mutual fund investors, providing support for overlapping board structures within fund families. However, the overlapping board structure is not free of criticism. One concern is that busy boards may not be effective monitors (Fich and Shivdasani, 2006). The workloads of mutual fund directors, particularly those that advise and monitor a significant number of funds, can be substantial because each fund has its own lengthy prospectus, regulatory filings and compliance issues to review. John Bogle, the founder and retired CEO of Vanguard, said “The required reading underscores the challenge. Mutual fund directors are either not being paid nearly enough for what they should be doing—or far too much for what they actually do.”1 In line with such concerns, Ferris and Yan (2007) present evidence that director busyness is associated with higher mutual fund fees. Another concern is that director overlaps may exacerbate the agency conflicts between mutual fund investors and fund families. Strategic performance transfer from low-value to high-value funds within a family is a documented issue in the mutual fund industry (Gaspar, Massa and Matos, 2006).2 However, it is essential to note that each fund that operates under the umbrella of a mutual fund family is a separate legal entity with its own set of investors, and the different classes of each mutual fund attract different types of investors. As each fund may have different objectives and dissimilar investors, it may be difficult for a single board to serve simultaneously and effectively the interests of the investors of each fund within a family. A 1 “Is Your Fund’s Board Watching Out For You?,” available at http://online.wsj.com/articles/SB10001424052702303753904577450243418998540. 2 The SEC explicitly mandates that that mutual fund boards must monitor to guard against cross-subsidization. These rules can be viewed at https://www.sec.gov/rules/final/finend.txt. 2 single board overseeing multiple funds may make it easier for mutual fund families to strategically transfer performance across member funds to favor those funds that are more likely to increase overall family profits. Given that the overlapping board structure may offer both benefits and costs, it is unclear if it is ultimately in the interest of mutual fund investors for boards to advise and monitor simultaneously multiple funds within a family. Board overlaps in mutual fund families have attracted attention of the media and legal experts3, but the academic research on the topic remains limited. In this paper, we perform a comprehensive analysis of the impact of overlapping boards within the mutual fund industry. We present evidence of the relationship between board structure and mutual fund characteristics such as fees, returns, net asset flows, as well as hidden actions of fund managers such as window dressing and cross-fund subsidization. Our sample consists of 3,948 domestic U.S. equity funds that contain 11,302 mutual fund-classes, which belong to 332 distinct fund families. The mean (median) fund family in our sample operates 164 (123) funds. We build a unique dataset of mutual fund directors using the certified shareholder reports and prospectuses filed by mutual funds that are available at the SEC Edgar database, and develop measures for the extent of director overlap in mutual fund families. Our first measure captures whether the fund family has a unitary board structure (i.e., complete overlap) as in Kong and Tang (2008). 60 percent of the funds in our sample of equity funds belong to families that follow a unitary board structure. 3 For example, see “On Board, at a Mutual Fund,” Wall Street Journal, September 3, 2014, available at http://www.wsj.com/articles/on-board-at-a-mutual-fund-1409757187. 3 Mutual fund families that do not have a unitary board structure still exhibit a considerable overlap of directors serving on the boards of their individual funds.4 Therefore, we develop additional measures that capture the extent of director overlap. We calculate the percentage of funds in a family that each individual director oversees, and obtain the average of this ratio across all directors in each individual fund, and we call this variable the “Director Overlap Ratio.” For example, the Fidelity Blue Chip Value Fund has a director overlap ratio of 0.95, meaning that on average, the directors of this fund oversee 95 percent of all funds within the Fidelity family. Recognizing that some funds may be more important to a particular fund family because they manage larger assets, we also calculate an “Asset-weighted Director Overlap Ratio,” where we express each director’s overlap by weighting the percentage of a family’s assets that he/she oversees. Continuing with our example, for the Fidelity Blue Chip Value Fund, the asset-weighted director commitment ratio is 0.98, meaning that on average, the directors of the fund oversee 98 percent of the fund family’s assets. This measure is similar to Tufano and Sevick (1997)’s “board concentration” measure. We start our analyses by investigating the relationship between director overlap and mutual fund fees. If the overlapping board structure offers economies of scale and bargaining advantages with the fund service providers, and if these advantages are passed on to the fund investors, then there should be a negative relationship between measures of director overlap 4 Through talking with practitioners in the industry, we have learned that a departure from the unitary board structure occurs randomly. For example, in some instances a fund may need additional expertise on its board that no other director possesses. Or, it may need someone to assume an additional leadership role (e.g., leading the audit committee) that no current board member is willing to undertake. In other instances, a board member retires and is replaced by another director, but not all funds in the same family stand for election in that particular year. Finally, sometimes, the departure from the unitary board structure occurs as a result of a merger with another fund. 4 and three types of fund fees: expense ratios, total fees and marketing and distribution (12-b1) fees. We present evidence for a negative relationship between board overlap measures and expense ratios and total fees – that is, funds that belong to mutual fund families with higher degrees of director overlap charge lower fees to their investors. This result is consistent with the findings of Tufano and Sevick (1997) and Kong and Tang (2008). However, marketing and distribution fees (12b-1 fees) do not appear to be lower in the presence of higher director overlap. 12b-1 fees include fees paid for marketing and selling fund shares, such as compensating brokers and others who sell fund shares, and paying for advertising, the printing and mailing of prospectuses to new investors, and the printing and mailing of sales literature.5 These fees have been criticized as being the least transparent cost component for mutual fund investors, and the SEC asked whether they result in “investors overpaying for services or paying for distribution services that they may not even know they are supposed to be getting.”6 It has also been shown that mutual fund companies selectively advertise their better-performing funds (Koehler and Mercer, 2009). We obtain complementary evidence from examining management fees as they are unrelated to board overlap, which suggests overlapping boards might not generate economies of scale. Next, we investigate the relationship between board overlap and returns to the fund investors. We analyze returns net of fees, gross returns, as well as fund alphas. We find no 5 A detailed description of these fees can be found at http://www.sec.gov/answers/mffees.htm. 6 On July 21, 2010, the SEC proposed “Measures to Improve Regulation of Fund Distribution Fees and Provide Better Disclosure for Investors.” See http://www.sec.gov/news/press/2010/2010-126.htm 5 significant correlation between director overlap and fund returns.7 This evidence suggests that lower fees are not passed onto fund investors in the form of higher net returns. The results we have summarized so far relate to the differences between funds with different director overlaps, but do not necessarily compare the funds that operate under the umbrella of the same fund family. Thus, next, we ask a related but different question that has not been investigated in the extant literature: If two funds that operate in the same family have different degrees of director overlap, are there differences in their fees and returns? We believe this is a more important question to answer from the fund governance perspective as a well-functioning board should look after the fund’s investors and not put the interest of the fund family before the interests of the individual fund’s interests. Recognizing this, the SEC rules that “ … the board should focus, among other things, on the relationship among the (fund) classes and examine potential conflicts of interest among (fund) classes regarding the allocation of fees, services, waivers and reimbursements of expenses, and voting rights.”8 To compare the funds with the rest of the funds in their families, we include family fixed effects in our regressions. If overlapping directors provide economies of scale, then we expect to see lower fees for funds that share more directors with the rest of the funds in the family (i.e., higher director overlap). Once we control for family fixed effects, we find no significant relationship between director overlap measures and fund expense ratios or total fees. The 7 Ding and Wermers (2012) state that unitary boards affect fund performance negatively. However, they define “unitary board” differently - as having at least two board members who are on at least one other fund board within the same management company. This may be a reason behind the differences in our results as their term “unitary board” is more similar to all of our other measures that capture incomplete board overlaps within a fund family. 8 https://www.sec.gov/rules/final/finend.txt. 6 mutual funds that share more directors with other funds in their fund families do not seem to pass on to their shareholders any of the supposed cost savings that may stem from economies of scale and/or greater bargaining. Furthermore, we find that 12b-1 fees are significantly higher for funds with greater degrees of director overlap when compared to the rest of the funds in the family. However, we do observe weak evidence that the level of management fees may be lower when there is greater board overlap, suggesting there may be some economies of scale associated with the board overlap. We continue with studying the relationship between fund returns and net asset flows with director overlap within fund families. We find evidence for a positive relationship between director overlap and fund returns, measured as net or gross fund returns, when we include family fixed effects. Net asset flows, too, are positively related to our measures of director overlap. We recognize that the higher returns may reflect greater managerial skill, or it may stem from window-dressing and/or cross-fund subsidization. If we find evidence for managerial skill, then we can argue that overlapping boards are effective governance structures. However, if we find evidence for window dressing and/or cross-fund subsidization, overlapping boards need to be approached with caution. Following Kacperczyk, Sialm and Zheng (2008), we construct the return gap to gain insight into whether the overlapping boards are able to help the funds employ more skilled managers. However, we observe a consistently insignificant relationship between the return gap, which is a proxy for managerial skill, and director overlap in our regressions. This result does not support the claim that the unitary boards attract more skilled managers. We then look into window dressing using the Agarwal, Gay and Ling (2014) measure 7 that captures the extent to which window dressing occurs at a fund – the backward holdings return gap. We find a significant and positive relationship between director overlap and window dressing. Another detrimental hidden action may be strategic performance transfer from one fund to another. Gaspar, Massa and Matos (2006) show that mutual fund families strategically transfer performance across member funds to favor those more likely to increase overall family profits. Families routinely charge different levels of fees on various member funds within the family, and also on different classes of each of those funds. Since investors tend to steer new monetary inflows to funds with higher past performance, mutual fund families may strategically transfer assets to those funds that have greater income generating potential for the family. Therefore, one example of strategic performance transfer would be from low-fee funds to highfee funds within a family. Overlapping boards may make it easier to steer investment opportunities to star funds that are attracting greater investor inflows or that generate more income for the fund family. For this reason, we study strategic performance transfer by closely following the empirical strategy of Gaspar, Matsa and Matos (2006), and find that this practice occurs more often when the high-fee funds have higher board overlaps. Interestingly, we do not observe strategic performance transfer when the low-fee funds have less director overlap with the rest of the funds in the family. We interpret this result to mean that having a director that is independent of the rest of the funds in a family protects the interest of shareholders of the low-fee funds. To summarize, these results present a picture that overlapping boards appear to be a benefit for mutual fund investors as costs are unaffected while returns may be higher. 8 However, by examining the hidden actions of funds, we present evidence for window dressing and cross fund subsidization at funds with greater degrees of director overlap. The cluster board structure appears to serve the interests of the fund family. Given that the SEC has mandated that boards look out for the interests of investors in specific fund classes, there is now a clear mismatch between the board’s raison d’etre and fund performance. Interlocking directorates may include directors who have a greater sense of duty towards the management company that compensates them and not to the shareholders they represent. Our research contributes to the literature on mutual fund governance. Most of the attention in this literature has been on the independence of the board of directors, and we are only aware of two studies that examine the effects of board overlap. Kong and Tang (2008) study the impact of unitary boards, and they present evidence for a negative relationship between fund expenses and unitary boards. Since their measure of board overlap does not vary between funds in a fund family, they are only able to compare funds in families with and without complete board overlap. Tufano and Sevick (1997) is more similar to our study in that they develop several measures that capture incomplete overlap between boards within a single family. We extend their analysis to show that unobserved family heterogeneity changes the effects of the board overlap. Our significant contributions to the literature are to illustrate how different degrees of overlap impacts fund characteristics by developing multiple nuanced measures of board overlap within a fund family, and to include family fixed effects to capture previously unobserved fund family heterogeneity. 2. Data 2.1. Sample Formation 9 The sample consists of U.S. equity mutual funds with Lipper asset codes marked as “EQ” in the Center for Research in Securities Prices (CRSP) Mutual Fund Database in 2007. This database covers U.S. open-end mutual funds and provides information on fund characteristics including returns, total net assets, fees, and investment objectives. Since our focus is actively managed mutual funds, passively managed funds such as index funds are excluded from the sample. For each individual fund, we manually identify its ultimate fund family.9 The final dataset contains information on 3,948 funds that contain 11,302 individual fund-classes and belong to 332 mutual fund families. We collect the board data at the fund-class level, because the SEC explicitly mandates that the mutual fund directors have fiduciary responsibilities for shareholders at the fund-class level not the fund itself.10 2.2. Database of Mutual Fund Directors We use publicly available certified shareholder reports (N_CRS) and prospectuses (485BPOS) to build a unique database of directors for each fund-class in 2007. These reports are available at the SEC Edgar database. For each individual mutual fund we record the names of directors, their tenure on the board, whether the person is CEO, their independence status, the size of the board, and whether the chairman of the board is independent of the fund 9 Kuhnen (2009) provides detailed description of the fund family structure and we follow her methodology in identifying the ultimate fund families. 10 The SEC has stated, “Consistent with its oversight of the class system and its independent fiduciary obligations to each class, the board must monitor the use of waivers or reimbursements to guard against cross-subsidization between classes. In making its findings, the board should focus, among other things, on the relationship among the classes and examine potential conflicts of interest among classes regarding the allocation of fees, services, waivers and reimbursements of expenses, and voting rights.” The complete text can be accessed at https://www.sec.gov/rules/final/finend.txt. 10 management company. As per the Investment Company Institute (ICI) we consider a director to be independent if the individual has not had a significant business relationship with the fund’s adviser, distributor or affiliates for at least two years, and does not own any stock of the investment advisor or certain related entities. 2.3. Measures of director overlap in mutual fund families We develop five measures of the director overlap within a fund family. We now describe these measures in detail. In Table 1, we provide the summary statistics. 2.3.1. Unitary Board Our first measure, unitary board, is an indicator variable that takes the value one if all of the individual funds in a fund family are overseen by the same group of directors (i.e. complete director overlap) and zero otherwise. This is the measure that is employed in Kong and Tang (2008). 60 percent of the fund-classes in our sample had a unitary board structure in 2007. 2.3.2. Director Overlap Ratio Fund families that do not have unitary boards still exhibit a significant director overlap, with common directors serving on boards of multiple fund-classes within the family. The next four measures are formulated to quantify the degree of director overlap for these funds. We first count the number of fund-classes in the fund family that each individual director oversees and then scale the sum by the total number of fund-classes in the family. We then obtain the average value across all directors in each mutual fund. Formally, for each fundclass with N individual directors, we estimate: 11 π 1 ππ’ππππ ππ ππ’ππ − ππππ π ππ π‘βππ‘ ππππππ‘ππ π ππ£πππ πππ π·πππππ‘ππ ππ£πππππ π ππ‘ππ = ∑ π πππ‘ππ ππ’ππππ ππ ππ’ππ − ππππ π ππ ππ π‘βπ ππππππ¦ π=1 This variable corresponds to the average percentage of funds in the family that the directors of an individual fund oversee. Note that for unitary boards, this measure would be one. The mean value of “Director Overlap Ratio” is 0.90 in our sample, meaning that the directors of a fund, on average, serve together on 90% of all boards within their families. We note, however, that there is considerable heterogeneity among this variable: the minimum value of this variable is 0.47%. We also calculate the average Director Overlap Ratio for each fund family, “Director Overlap Ratio (Family)”. This is accomplished by first calculating the director overlap ratios for individual fund classes in a family (i.e. director overlap ratio), and then taking the averages. This family-level board overlap measure has an average value of 90.3%, and as expected is highly correlated with the director overlap ratio. 2.3.3. Asset-weighted Director Overlap Ratio This measure focuses on the monetary value of the fund assets that are overseen by a director to capture the importance of the funds a director oversees within the fund family, since funds that attract larger assets might be more valuable to the fund families. We sum up the assets of funds in the fund family that each individual director oversees and scale it by the total assets of funds in the family, and then average the measure across all directors in each mutual fund. Formally, for each fund-class with N individual directors, we estimate: 12 π΄π π ππ‘ − ππππβπ‘ππ π·πππππ‘ππ ππ£πππππ π ππ‘ππ π ∑ πππ‘ππ πππ‘ ππ π ππ‘π π‘βππ‘ ππππππ‘ππ π ππ£πππ πππ 1 = ∑ π πππ‘ππ πππ‘ ππ π ππ‘π ππ π‘βπ ππ’ππ ππππππ¦ π=1 This variable is estimated at the fund-class level and corresponds to the average percentage of assets in the family that the fund’s directors oversee. Note that for unitary boards, this measure would be one. This measure is similar to Tufano and Sevick (1997)’s measure “board concentration.” The mean (median) value of this variable is 90% (100%). Finally, we look at the same concept of value-weighting each director from the perspective of the fund family. The measure is estimated by averaging the asset-weighted director overlap ratios across all funds within a fund family. This measure is similar to Tufano and Sevick (1997)’s measure “sponsor concentration.” The average value is 90.4% which is slightly higher than the raw frequency with which directors serve together on multiple boards within the family. This reflects both the fact that directors typically serve simultaneously on the boards of all classes of a particular mutual fund and that larger funds often have more classes, and that larger fund families are more likely to have overlapping boards. This variable has a mean (median) value of 90% (100%). 2.4. Fund Characteristics We obtain data on fund characteristics from CRSP Mutual Funds Database for 20072010, including net asset values, expense ratios, front and rear-load fees, net returns and portfolio holdings. We list the variable names and descriptions in Appendix II. In Table 2, we present the descriptive statistics for fund characteristics. 13 Fund size is measured as the total net assets under management (mtna). We calculate the average monthly total net assets over a calendar year for each fund. Fund family size is the total net assets under management of all funds within a mutual fund complex. Both fund and fund family size capture possible economies of scale as the size of a fund may affect its ability to make purchases or sales with minimal impact on market price (Ferris and Yan, 2007). The mean (median) size of a mutual fund is $431 mn ($32mn). Total asset inflows are measured as the annual change in total assets under management. The mean (median) value of net asset inflows is -$14mn ($0mn). Fund age is estimated as the number of years since a fund was first offered to investors. It is used as a control variable, because the needs of a fund have been found to vary predictably over the fund’s lifecycle (Tufano and Sevick, 1997; Del Guercio et al., 2003; Ferris and Yan, 2007). The mean (median) fund age is 9.4 years (8.0 years). We examine separately three types of fees: expense ratios, 12b-1 or marketing and distribution fees, and total fees. First, the expense ratio is the ratio of total operating expenses to assets under management. We find that the sample mean (median) expense ratio is 135.18 bp (130 bp). Second, the mean (median) 12b-1 fee is 58.91 bp (50.00 bp). Finally, to calculate the total fees faced by a representative investor in a mutual fund class, we add the annualized front and rear-end loads to the expense ratios. Following Sirri and Tufano (1998), we assume that the average investor remains invested in the fund for a period of seven years. Higher fees are consistent with the management retaining a higher fraction of fund income and inflows (Kuhnen, 2009). The sample mean (median) total fees is 145.69 bp (144bp). 14 To calculate the net returns, we calculate fund performance in year t by compounding monthly returns from CRSP (mret) over the entire year. Net returns are net of all management expenses and 12b-fees, as well as front and rear load fees. The sample mean (median) fund generated returns of 520 bp (1,217 bp). Gross returns, which are defined as net returns plus total fees, have a mean (median) value of 443 bp (1,168 bp). We estimate alpha using a four factor regression analysis of monthly data as this dataset consists exclusively of equity funds. We use the three Fama and French (1992) factors – excess return on the CRSP value-weighted index, difference in returns between a small and large stock portfolio, and difference in returns between a high and low equity to book market portfolio – and the Carhart (1997) momentum factor. Thus, the estimated alpha is a measure of the annual abnormal return associated with each mutual fund. The mean (median) value of alpha is 2.20 basis points (20.42 bp). The return gap is calculated as per Kacperczyk, Sialm, and Zheng (2008) and is used as a measure of managerial skill. It is calculated as the difference between a fund’s actual performance from the performance of the fund’s previously disclosed portfolio on the assumption the previously disclosed portfolio was actually held throughout the quarter. The mean (median) value of the return gap is 0.0003 basis points (0.0001 bp), similar in magnitude to the statistics provided by Agarwal et al. (2014). The window dressing measure is based on Agarwal, Gay and Ling (2014). It is measured as the difference between the returns that would have been generated by the reported quarter-end portfolio had it been held throughout the quarter and the fund’s actual 15 performance. The mean (median) value of the window dressing measure is 0.0022 basis points (0.0011 bp), comparable to the sample statistics in Agarwal et al. (2014). 3. Results without Family Fixed Effects 3.1. Director Overlap and Mutual Fund Fees We first investigate the relationship between the extent of board overlap in mutual fund families and mutual fund fees charged to investors. One of the main responsibilities of the board is to negotiate fees. Hence, lower fees may signal greater board effectiveness (Del Guercio et al., 2003). More importantly, unitary board structure is thought to be associated with lower fees due to the economies of scale and bargaining power advantages that such structure may provide (ICI, 2009; Kong and Tang, 2007). To examine the relation between board overlap and mutual fund fees, we estimate the following equation: πΉπ’ππ πΉπππ π,π‘ = πΌ + π½π·πππππ‘ππ ππ£ππππππ.2007 + πΎ πππ‘ + πΏπ π‘π¦ππ + ππ‘ + ππ,π‘ [1] We employ three separate measures for fund fees: the expense ratio, 12-b1 fees and total fees. The control variables include the size of the fund and the fund family, age of the fund and the fund family, and two other board characteristics that have been show to affect mutual fund fees – board size and board independence and CEO-chairman duality. Fund and family size control for possible economies of scale, and have been shown to be inversely related to fund fees (e.g. Khorana, Servaes and Tufano, 2008; Kuhnen, 2009). The fund’s age is used to capture the lifecycle effect whereby the needs of a fund vary predictably according to its age 16 (Tufano and Sevick, 1997; Del Guercio, Dann, and Partch, 2003; Ferris and Yan, 2007). Year and Lipper investment objective fixed effects are included in the regressions. We estimate Equation 1 using weighted least squares (WLS) estimations, where the weights are the share of a fund family in the total number of observations in the sample. Using these weights mitigates potential heteroskedasticity. Standard errors are clustered to control for possible correlation across observations belonging to the same fund family. 3.1.1. Expense Ratios Expense ratio represents the percentage of assets deducted for fund expenses and measures the annual expenses of a fund. These expenses include the management fees, administrative fees, operating costs, 12-b1 fees (marketing and distribution costs), and all other asset-based costs incurred by the fund. Controlling for observable characteristics that correlate with how difficult it is to operate the fund (such as its size and investment objective), a higher expense ratio indicates that more of the rents are captured by the management, and less by fund investors (Kuhnen, 2009). The results are presented in Table 2. We begin by examining the impact of a fund family adopting a unitary board structure for all funds within the family (Column I). The results indicate that expense ratios are lower when a fund family has greater director overlap. If a fund has a one standard deviation increase in the director overlap ratio, it will experience a decrease in total fund fees of -26.79*0.20 or 5.36 basis points. Given that the average fund expense ratio is 135 basis points, this would correspond to a 4% decrease in expense ratios. 17 3.1.2. Total Fees Next, we investigate the relationship between total fees – expense ratios plus total load fees – and board overlap. The results are presented in Table 3, and are parallel to the results reported above about expense ratios - that total expense ratios are lower when a fund has greater director overlap with the rest of the funds in its fund family. If a fund has a one standard deviation increase in the director overlap ratio, it will experience a decrease in total fund fees of -30.13*0.20 or 6.03 basis points. Given that the average fund fees are 154 basis points, this would correspond to a 3.9% decrease. 3.1.3. Marketing and Distribution Costs (12-b1 fees) We next analyze the relationship between board overlap and marketing and distribution fees (12b-1 fees). 12b-1 fees include fees paid for marketing and selling fund shares, such as compensating brokers and others who sell fund shares, and paying for advertising, the printing and mailing of prospectuses to new investors. These fees have been criticized as being the least transparent cost component for mutual fund investors, and the SEC asked whether they result in “investors overpaying for services or paying for distribution services that they may not even know they are supposed to be getting.” It has also been shown that mutual fund companies offer biased snapshots of their success by selectively advertising their higher performing funds (Koehler and Mercer, 2009), and that funds that advertise attract 20% more new inflows than comparable funds that do not advertise (Jain and Wu, 2000). Therefore, in order to attract more asset inflows, fund families may find it beneficial to engage in selective advertising, but at the cost of funds’ existing investors. 18 We present these results in Table 4. We find that the 12b-1 fees are lower for funds that operate in fund families with greater director overlap (Columns I, III and V). For example, the coefficient on the unitary board dummy is -12.78 and is significant at the five percent level. According to this coefficient, investors of funds that operate in families with a complete director overlap pay 12.78 basis points less in 12b-1 fees. However, the coefficient on the director overlap ratios in columns II and IV are insignificant. 3.1.4. Management Fees One of the largest components of the expense ratio is the management fee. In our dataset the mean (median) values of the management fees and expense ratio are 49.21 bps (67.30 bps) and 135.18 bps (130.00 bps), respectively. By law, the board and fund management companies are required to renegotiate the management fee structure every year. If the overlapping board structure does indeed possess the hypothesized bargaining advantages, then an overlapping board should have a decreasing cost curve and thus be associated with lower management fees. Thus we will interpret a negative (positive) relationship between management fees and board overlap as confirmation of a bargaining advantage (self-dealing tendency). We present the results in Table 5. We find that there is no significant relationship between management fees and board overlap when we compare funds across families. This suggests that while unitary and overlapping boards may possess some bargaining advantages, these advantages are clouded by the presence of agency problems as directors neglect their fiduciary responsibilities to investors. We do note that the coefficients are all negative, 19 although consistently statistically insignificant, which provides some anecdotal confirmation of the belief that there are bargaining advantages. We note that the two prior papers on board structure – Tufano and Sevick (1997) and Kong and Tang (2008) – did not examine management fees and thus we cannot benchmark our results against theirs. 3.1.5. Control Variables As our control variables have consistent signs and interpretations across these various models analyzing fees, we discuss them here for all the models reported above. Fund age is consistently positive and statistically significant in all models examined thus far. This suggests that more experienced funds charge higher fees, which is consistent with the possibilities that fund families are subsidizing younger or newer funds or charging higher fees for the funds with more established reputations. We observe that there are generally economies of scale as fund size is negative and statistically significant in analyses of most types of fees. The exception is that fund size is positively associated with management fees. These results suggest that while there are economies of scale associated with fixed expenses at the fund level (e.g., operating and marketing), there may be greater potential for the family to charge more for management at funds that have more assets under management. Additional support for the presence of economies of scale in fund operating expenses and management is obtained from the family size variable. However, we note that this effect is not present in the analysis of 12b-1 fees, which suggests that families may coordinate marketing and distribution strategies across funds. 20 We find that board size is consistently positively associated with higher fees although we note that this relationship is not always statistically significant. Meanwhile, board independence is consistently insignificantly associated with all types of fees. These results suggest that smaller boards are more effective, consistent with the broader literature on corporate boards in general (Yermack, 1996) and in the mutual fund context (e.g., Tufano and Sevick, 1997). 3.2. Director Overlap and Mutual Fund Performance In this section, we analyze the relationship between director overlap and fund performance. Overlapping boards are believed to possess bargaining advantages that enable the family to attract higher skill managers. If overlapping boards deliver such bargaining advantages to funds, then there should be a positive association between fund performance and our director overlap ratios. We estimate the following equation to examine the relationship between fund performance and director overlap: πΉπ’ππ πππππππππππ π,π‘ = πΌ + π½π·πππππ‘ππ ππ£ππππππ.2007 + πΎ πππ‘ + +πΏπ π‘π¦ππ + ππ‘ + ππ,π‘ [2] We use three measures for fund performance: net returns, gross returns and fund alphas. Net and gross returns capture the year-on-year changes in mutual fund value with and without consideration of fees paid by the representative investor. Fund alphas capture fund performance on a risk-adjusted basis and are calculated using Carhart’s (1995) 4-factor model. We do not analyze style-adjusted fund returns in either specification as per Gormley and Matsa (2014). 21 In Table 6, we present the results for net returns. The evidence in the previous section and in the extant literature (Kong and Tang (2007)) suggests that overlapping board structure is associated with lower costs. If these cost savings are passed on to the mutual fund investors as a result of an effective governance mechanism, then director overlap would also be associated with higher net returns. However, we find that the coefficients on director overlap measures are not statistically significant, which runs contrary to this hypothesis. In Tables 6 and 7, we analyze the relationship between gross returns and alphas and our board overlap measures. Once again, we do not observe any significant relationship between gross returns and board overlap (Table 7) and fund alphas and board overlap (Table 8). The results are in line with Kong and Tang (2008). 3.3. Summary The aim of this section was to align our study with the previous literature that look into board overlaps without incorporating the family fixed effects. To summarize, we find that director overlaps in mutual fund families are associated with lower fees, and there are no significant differences in fund returns. These findings are in general consistent with the conventional wisdom that overlapping boards can identify and exploit economies of scale and possess bargaining advantages. Tufano and Sevick (1997) and Kong and Tang (2008) present similar results. 4. Results: Within-Family Differences The results we have presented so far relate to the differences between funds with different degrees of director overlaps in general. However, they do not necessarily compare the funds 22 that operate under the umbrella of the same fund family with one another. Thus, next, we ask a related but different question that has not yet been investigated in the extant literature11: If two funds that operate in the same family have different degrees of director overlap, are there differences in their fees and returns? We believe this is a more important question to answer from the fund governance perspective. A well-functioning board should look after the fund’s investors and put the interest of the fund family before the interests of the individual fund’s interests. Recognizing this, the SEC rules that “ … the board should focus, among other things, on the relationship among the (fund) classes and examine potential conflicts of interest among (fund) classes regarding the allocation of fees, services, waivers and reimbursements of expenses, and voting rights.” To compare the funds with the rest of the funds in their families, we include family fixed effects in our regressions. We note that once the family fixed effects are included in the regressions, we can only examine the two measures of director overlap that are estimated at the fund level (i.e., paralleling the results reported in Columns II and IV in Tables 2-7). 4.1. Fees We start by analyzing fund fees. If the economies of scale and bargaining advantages are present, then we expect to find lower fees for the funds with a greater degree of director overlap with the rest of the funds in the family. The difference in this regression equation from Equation [1] is the inclusion of family fixed effects. By including the family fixed effects, we are 11 Tufano and Sevick (1997) report results using family fixed effects, however since their dataset is not a panel, sponsor-specific variables such as sponsor size can not be included in the regressions. 23 comparing two funds within the same family and answering the following question: If two funds within the same family have different degrees of director overlap, does the fund with higher overlap enjoy greater economies of scale, which is translated in lower fees? πΉπ’ππ πΉπππ π,π‘ = πΌ + π½π·πππππ‘ππ ππ£ππππππ.2007 + πΎ πππ‘ + πΏπ π‘π¦ππ + πππππππ¦ + ππ‘ + ππ,π‘ . [1’] We use four measures of fund fees as the dependent variable: expense fees, total fees, 12b-1 fees, and management fees. We present the results in Table 9. First, we observe that there is no significant relationship between expense fees and director overlap. It could be that once we control for unobserved heterogeneity, there are no economies of scale that could be transferred to shareholders as lower fees. Alternatively, the lack of significance may mean that the economies exist but are not being shared among all of the funds, or fund classes, within the family. In any case, these results cast doubt on the argument that unitary boards are favorable for mutual fund investors. Next, we also identify no significant relationship between total fees and board structure. Thus we conclude that mutual fund investors do not face different fee structures due to the nature of director overlaps within the fund family. Next, we observe that 12b-1 fees are significantly higher when there is higher director overlap. These results suggest that boards of directors may approve higher 12-b1 fees whenever the directors are cognizant of how the funds might be used by other funds within the family, given their inside knowledge of the needs of other funds. Finally, we obtain evidence that management fees may be lower in the presence of greater board overlap but this does not hold when the board overlap measure is asset-weighted. This set of results suggests that the 24 potential for economies of scale or bargaining advantages does exist when a fund family has overlapping boards, but that this is less likely to occur as the directors represent increasingly large funds within the family. 4.2. Fund Performance To examine the relationship between fund performance and director overlap, we estimate the following model: πΉπ’ππ πππππππππππ π,π‘ = πΌ + π½π΅ππππ ππ£ππππππ.2007 + πΎ πππ‘ + πΏπ π‘π¦ππ + πππππππ¦ + ππ‘ + ππ,π‘ [2’] We present the results in Table 10. Once we control for family fixed effects, we observe a highly positive and statistically significant relationship between net returns and board overlap. Moreover, when we control for family heterogeneity to capture the possibility that directors are a conduit of information between funds within a family or are able to negotiate preferential cost structures for the fund, we identify a highly positive and significant impact of board structure upon gross returns. Thus, we are able to observe that boards of directors can have both a direct and an indirect effect upon the performance of the fund with the direct effect working through the fees channel and the indirect effect occurring through information transmission. We also note that when family fixed effects are included in the model, the impact of family size disappears entirely while board size becomes positively associated with higher alpha. 4.3. Summary – within-family effects 25 When we control for family fixed effects, we find that funds with higher director overlap do not charge lower fees as it has been shown in previous literature (Tufano and Sevick, 1997; Kong and Tang, 2008) and confirmed in our regressions without family fixed effects in Section 3. However, we find that funds with higher director overlap outperform the funds with lower director overlap. Both gross returns and returns net of fees are higher for funds that exhibit a higher degree of director overlap within their families. In the next section, we try to understand the sources of higher returns. 5. Sources of higher disclosed fund returns We argue that the higher reported returns may be either due to managerial skill, or due to unobserved actions of the fund managers such as window dressing (Agarwal, Gay and Link, 2014), or performance transfer from low-value funds to high-value funds within a fund family with the aim of increasing the overall asset flows to the fund family (Gaspar, Matos and Massa, 2006). In this section, we look into these three channels. If overlapping boards provide effective governance mechanisms for the individual funds that they have fiduciary duties for, then we should observe a positive correlation between managerial skill and board overlap. If on the other hand, we find evidence for window dressing and/or strategic performance transfer, then their effectiveness is questionable. Moreover, if there is significant window dressing and/or strategic performance transfer, there is a moral hazard problem that reflects the fact that board members may be more likely to retain their seats if the fund family overall benefits even as the board members are supposed to look out only for the interests of the investors. 26 5.1 Managerial Skill We first look into whether board overlaps are associated with the employment of higher skilled fund managers. A measure of managerial skill is suggested by Kacperczyk, Sialm, and Zheng (2008). They argue that a fund’s disclosed performance record would correspond imperfectly with the hypothetical performance that would have been generated if the fund had actually held the publicly disclosed holdings for the reporting period. This reflects the fact that in between disclosure dates, the fund managers have the ability to trade repeatedly and alter the composition of their portfolios. Kacperczyk et al. (2008) propose “return gap” as a proxy for managerial skill. In calculating the return gap, they presume that the disclosed beginning-ofquarter portfolio is held for the subsequent quarter, and calculate the difference between the disclosed returns and the hypothetical return if the beginning-of-quarter portfolio was held during the quarter. A larger return gap implies that a manager’s decisions to alter the disclosed portfolio resulted in higher performance, and therefore suggests higher managerial skill. Kacperczyk et al. (2008) find that the return gap is persistent and affects fund performance. We estimate the following regression equation to relate the managerial skill, as proxied by return gap, to director overlap. π ππ‘π’ππ ππππ,π‘ = πΌ + π½1 π·πππππ‘ππ ππ£ππππππ.2007 + πΎ πππ‘ + πΏπ π‘π¦ππ + πππππππ¦ + ππ‘ + ππ,π‘ . [3] If we find a positive impact of board overlap on the return gap, we could infer that overlapping board of directors are able to recruit more skilled managers, which would be consistent with the board successfully fulfilling their governance roles. 27 Board overlap appears to be insignificantly associated with the return gap, as shown in Table 11, columns I and II. This finding is consistent with the idea that board is not effective in selecting high skill fund managers, and/or monitoring individual managers once they are selected. 5.2 Window Dressing Window dressing is an agency problem that involves managers altering fund portfolios by disclosing disproportionately higher (lower) holdings in stocks that have done well (poorly) over a reporting period to mislead investors about their true ability (Agarwal, Gay and Ling, 2014). Agarwal et al. develop a proxy for the extent of window dressing – the backward holding return gap, which is computed as the difference between the return imputed from the reported quarter-end portfolio and the fund’s disclosed quarterly return. The intuition is that a windowdressing manager will tilt portfolio holdings towards winner stocks and away from loser stocks to give investors a false impression of stock selection ability having observed the winner and loser stocks towards the quarter end. We compute the backward holding return gap as described in Agarwal et al, (2014) and estimate the following regression equation: π΅ππππ€πππ π»ππππππ π ππ‘π’ππ πΊπππ,π‘ = πΌ + π½1 π΅ππππ ππ£ππππππ.2007 + πΎ πππ‘ + πΏπ π‘π¦ππ + πππππππ¦ + ππ‘ + ππ,π‘ . [4] We find a positive and significant coefficient on the board overlap variable, implying that the funds with higher director overlap engage in more window dressing when compared to the funds in their families with lower degrees of director overlap (Column III). We note that we 28 do not find a significant coefficient of the asset-weighted overlap measure, but it remains positive. 6. Board Overlap and Strategic Performance Transfer in Mutual Fund Families There is considerable evidence that the mutual fund families follow strategies to maximize the returns to the family as a whole. For example, within mutual fund families, there are often funds that out-perform the rest of the family across time, and these can be termed “star funds”. Performance persistence is unusual within the fund industry as investment success is generally not likely to persist across multiple time periods (Brown and Goetzmann, 1995), therefore the existence of star funds is one sign that families may be purposefully allocating resources across funds in an unequal way (Guedj and Papastaikoidi, 2004). A star fund increases flows to all funds in the family (Nanda et al., 2004), and is thus of significant marketing and public relations value to the mutual fund family. Strategic cross-fund subsidization may occur whereby the fund family coordinates actions to systematically boost the performance of the funds with high family value at the expense of the funds with low family value. Gaspar et al. (2006) show that cross fund subsidization is a proxy for performance transfer as the mutual fund family reallocates “winners” to the better performing funds to ensure performance persistence. The fund family would benefit from future investor inflows if extra performance is directed towards the highfee funds. This could happen through the fund family coordinating purchases and sales of investments made by particular funds within the family. It could also happen if the family allocates IPO stocks differentially to the individual funds under its umbrella. 29 We hypothesize that if a low-value fund has a larger director overlap when compared to the high-fee funds, there will be more opportunities and incentives for strategic performance transfer from the low-fee fund to the high-fee fund. That is because the low-fee fund’s board would be less independent than the rest of the family, and may prioritize the fund family’s collective interests. Tufano and Sevick (1997) have shown that boards frequently discuss issues pertaining to multiple funds at a single board meeting. To test this hypothesis, we follow Gaspar et al. (2006) and test whether the observed differences in returns between high-fee funds and low-fee funds in a family systematically exceed the difference in returns of their investment styles. Specifically, we estimate the following regression: π»ππβ πππ‘ πππ‘π’πππ,π‘ πΏππ€ − πππ‘ πππ‘π’πππ,π‘ = πΌ + π½1 πππππΉπππππ¦π,π‘ + πΎ πππ‘ + πΏπ π‘π¦ππ + ππ‘ + ππ,π‘ . [5] “Same Family” is an indicator variable that takes the value 1 if the low value and high-value fund pairs (on the left-hand side of the above equation) belong to the same mutual fund family. These are called “actual pairs.” The indicator variable takes the value zero if the funds belong to different families. This is accomplished by replacing each low-value fund in an actual pair with a low-value fund from another family (matched pairs) that has the same investment objective. Μ1 is positive and significant, and infer from this result that fund Gaspar et al. (2006) show that π½ families strategically transfer performance from high-value funds to low-value funds. Our estimation results yield the same result – for our study sample, we too find a significant and positive coefficient on the “πππππΉππππ𦔠indicator (Table 12, Column 1). 30 Once we confirm the presence of such performance transfer from low-fee funds to high-fee funds within our study sample, we move on to investigate the effects of board overlap on performance transfer by estimating the following equation: π»ππβ πππ‘ πππ‘π’πππ,π‘ πΏππ€ − πππ‘ πππ‘π’πππ,π‘ = πΌ + π½1 πππππΉπππππ¦π,π‘ ∗ (πΏπππππ π·πππππ‘ππ ππ£πππππ ππ‘ π‘βπ π»ππβπππ ππ’ππ) + π½2 πππππΉπππππ¦π,π‘ ∗ (πΏπππππ π·πππππ‘ππ ππ£πππππ ππ‘ π‘βπ πΏππ€πππ ππ’ππ) + πΎ πππ‘ + πΏπ π‘π¦ππ + ππ‘ + ππ,π‘ [5] This regression equation augments Equation 4 by incorporating the board structure. “πΏπππππ π·πππππ‘ππ ππ£πππππ ππ‘ π‘βπ π»ππβπππ ππ’ππ” is an indicator variable that takes the value one if the high-fee fund in the actual pair has a greater director overlap ratio than the low-fee fund, and zero otherwise. Similarly, πΏπππππ π·πππππ‘ππ ππ£πππππ ππ‘ π‘βπ πΏππ€πππ ππ’ππ is a variable that takes the value one if the low-fee fund in the actual pair has a greater overlap ratio than the high-fee fund, and zero otherwise. Μ1 would indicate that there is performance A significant and positive estimated coefficient π½ transfer from low-fee funds to high-fee funds when there is greater director overlap at the high-fee funds. These would be the instances when the low-fee funds do not have many directors that are independent of the high-fee funds. On the other hand, a significant and Μ2 would be evidence of performance transfer from high-fee funds to low-fee funds positive π½ when the director overlap measure is higher at the low-fee funds. In such cases, the low-fee funds have additional directors that do not serve on the board of the high-fee funds, and may be more inclined to protect the interests of the shareholders of low-fee funds rather than maximizing the family values by transferring performance to the high-fee funds. 31 The evidence supports our predictions. We find that the magnitude of the performance increase at high fee funds is both highly statistically significant and large in magnitude, 59.2 bp, while the low fee fund has a statistically insignificant change in performance (Table 12, column II). Altogether, these results suggest that high fee funds are consistently enjoying a 50-60 basis point increase in net returns due to board overlap. Given that the average net return in our dataset is 520 basis points, this is roughly a 10% increase. These results suggest that the board overlap leads to within family performance transfers, which benefit investors in high-fee funds through higher returns, while steering performance away from low-fee funds. 7. Asser inflows Given that the presence of a board overlap is associated with strategic performance transfer to higher fee funds, and that fund families selectively advertise star funds, we expect that board overlap should lead to higher asset inflows for individual funds within the family. We therefore examine a model that explores whether this is the case for individual fund-classes: π΄π π ππ‘ ππππππ€π π,π‘ = πΌ + π½1 π΅ππππ ππ£ππππππ.2007 + πΎ πππ‘ + πΏπ π‘π¦ππ + πππππππ¦ + ππ‘ + ππ,π‘ . [6] We find that there is a positive effect of board overlap upon asset inflows (Table 10). This result implies that the family is able to use the board to coordinate the actions of individual funds through strategic performance transfer and window dressing to advertise the family as a whole. Accordingly, an overlapping board structure enjoys and leverages informational advantages as it can act as a conduit for sharing information across funds and managers within the family. This result suggests that the board is more focused on aggregate family benefits 32 than on the interests of investors in each class of each mutual fund, as is the official mandate of the board from the SEC. 8. Robustness Checks 8.1. Number of funds In our first round of robustness tests, we replace family size with the number of funds in a family and rerun all regressions. When we do this analysis it is necessary to exclude family size, because family size and number of funds in a family are highly correlated. This round of results allows us to control for fund family scope as proxied by number of funds. In a sense we are now testing the extensive margin of a mutual fund family, family scope, vs. the intensive margin, family size. These results are qualitatively similar to those described in this paper, and are available in our appendix. 8.2. Interactions of Director overlap measures with number of funds in the family The director overlap may be more problematic in bigger families that market a larger number of funds. Therefore, we repeat our analyses by adding the interaction of director overlap and number of funds in a family to our list of explanatory variables. The coefficients on the interaction terms are insignificant and the coefficients on the director overlap measures are qualitatively and quantitatively similar. 8.3. Using funds instead of fund classes It is common in the mutual fund literature for all empirical analyses to be conducted at the level of the fund, not the fund class. However, we conducted our analyses of mutual fund fees and returns at the fund class level to be consistent with the SEC requirement that board of 33 directors have a fiduciary responsibility to investors at the class level. While that is the case, it is also true that the managers comingle funds across classes and thus make decisions at the fund level. Accordingly, we replicated all results at the mutual fund level and obtained results that are qualitatively similar to those discussed earlier, and are available in our appendix. 8.4. Nonlinearity We also estimate an alternative specifications of the regression equation that allow for nonlinearity in the relation between dependent variables and board overlap. Our results do not indicate the presence of such non-linearities. 9. Conclusion Conventional wisdom suggests that a greater extent of board overlap within a mutual fund family will benefit investors through the presence of economies of scale and bargaining power advantages. However, as documented by Tufano and Sevick (1997) and Kuhnen (2009), boards of directors are initially appointed by the fund sponsor, and are generally asked to stay on for long periods of time. Accordingly, the directors may prioritize the interests of the fund family even as the SEC mandates that their fiduciary responsibilities lie at the fund-class level. Our first contribution is that we examine how variations in the extent to which boards overlap within a fund family affect fund characteristics by examining board overlap from angles that directly reflect both the busyness of the board to capture the scope of the demands on their time and the number and size of the funds to capture the intensity of these demands. Prior research has focused primarily on the case of complete board overlap, a unitary board, as in Kong and Tang (2008). 34 Our second contribution is to acknowledge that boards of directors often have connections that are not observed, and that each mutual fund family has a unique institutional culture that may foster different types of communication. Accordingly, we include family fixed effects in our analyses to reduce the impact of unobserved heterogeneity. This is similar to the approach adopted by Tufano and Sevick (1997). We illustrate that the conventional expectations for the impact of an overlapping board are not observed if we control for this heterogeneity. Finally, by examining multiple dimensions of board overlap, we identify clear relationships between board overlap and fund performance. Specifically, we find that funds with a higher degree of board overlap have higher marketing fees but not higher total fees. This is consistent with the fact that mutual fund families advertise star funds more than others, and board overlap is associated with higher net and gross returns. However, performance transfer to high fee funds is more likely to occur when there is board overlap. Overlapping boards may make it easier to steer investment opportunities to star funds that are attracting greater investor inflows or that generate more income for the fund family, because of their compensation practices. We conclude that unitary boards are a mixed blessing. 35 References Agarwal, Vikas, Gerald D. Gay, and Leng Ling, 2014, “Window dressing in mutual funds,” Review of Financial Studies, 27(11), 3133-3170. Brown, Stephen J., and William N. Goetzmann, 1995, “Performance persistence,” Journal of Finance, 50(2), 679-698. Chen, Joseph, Harrison Hong, Ming Huang, and Jeffrey D. Kubik, 2004, “Does fund size erode performance? 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Kuhnen, Camelia M., 2009, “Business networks, corporate governance, and contracting in the mutual fund industry,” Journal of Finance, 64(5), 2185-2220. Nanda, Vikram, Jay Wang, and Lu Zheng, 2004, “Family values and the star phenomenon: Strategies of mutual fund families,” Review of Financial Studies, 17(3), 667-698. Sirri, Erik R., and Peter Tufano, 1998, “Costly search and mutual fund flows,” Journal of Finance, 53(5), 1589-1622. Tufano, Peter, and Matthew Sevick, 1997, “Board structure and fee-setting in the U.S. mutual fund industry,” Journal of Financial Economics, 46, 321-355. Yan, Xuemin (Sherman), 2008, “Liquidity, investment style, and the relation between fund size and fund performance,” Journal of Financial and Quantitative Analysis, 43(3), 741-768. 37 Appendix. Variable Descriptions Variable Expense Ratio Definition Source Expense ratio of the fund in year t. Percentage of assets deducted CRSP for fund expenses, including 12bβ1 fees, management fees, administrative fees, operating costs, and all other assetβbased costs incurred by the fund. Portfolio transaction fees, or brokerage costs, as well as initial or deferred sales charges are not included in the expense ratio. Converted to basis points. Management Fee Fees paid out of fund assets to the fund's investment adviser or its CRSP affiliates for managing the fund's portfolio.Converted to basis points. 12 b1 Fees Reported as the ratio of the total assets attributed to marketing and CRSP distribution costs. Represents the actual fee paid in the most recently completed fiscal year as reported in the Annual Report Statement of Operations. Converted to basis points. Nonβdistribution Expenses CRSP Annual fund expenses (expense ratio) minus 12βb1 fees. The nondistribution expenses measure the costs of operating the fund (e.g., investment management, transfer agency, audit, etc.), excluding the costs of distributing the fund. Annual fund expenses plus the front and rearβend loads. CRSP Fund’s net return in year t, computed by compounding monthly net CRSP returns (retm). Expressed in basis points. Total Fees Net Return Gross Return Alpha Total Net Assets Net Asset Flows Fund Age Fund Size Return Gap Window Dressing Board Size Board Independence Director Overlap (Fund) Director Overlap (Family) Assetβweighted Director Overlap (Fund) Assetβweighted Director Overlap (Family) Fund’s gross return in year t, computed by adding total fees and Net CRSP Return. Expressed in basis points. Fund's alpha estimated using returns over 2007β2009 using Famaβ CRSP French 4 factor model Natural logarithm of fund total net assets (tna) in USD millions. CRSP TNA_flow = mtna β (mtna[_nβ1]*(1+mret)) CRSP Log of the age of the mutual fund, measured as the current year CRSP minus the year at which it was first offered Log of the total net assets for each fund in each year available, CRSP reported in millions of dollars Natural logarithm of number of directors on a fund's board of Handβcollected directors. Percentage of independent directors serving on a fund's board. The average percent of funds overseen by directors in this mutual Handβcollected fund, measured as the number of the funds overseen by a director in a family divided by total funds in the family, and then averaged across all directors in each mutual fund. Board overlap averaged over all funds in a family. Handβcollected The average percent of assets overseen by directors in this mutual fund, measured as the total net assets overseen by a director in a fund family divided by total fund family assets, averaged over all directors in the fund and all years available Assetβweighted board overlap averaged over all funds in a family. Handβcollected Handβcollected Table 1. Summary Statistics This table presents the summary statistics for board characteristics and fund characteristics for U.S. equity mutual funds for 2007β2010. All variables are defined in the Data Appendix. Panel A. Board Characteristics Unitary Board Director Overlap Ratio (Fund) Director Overlap Ratio (Family) Assetβweighted Director Overlap (Fund) Assetβweighted Director Overlap (Family) Board Size Board Independence Mean Std. Dev. Median 0.59 0.90 0.90 0.90 0.90 8.61 0.82 0.49 0.20 0.18 0.21 0.18 2.61 0.10 1.00 1.00 1.00 1.00 1.00 8.00 0.83 Mean Std. Dev. Median p25 p75 min max β 0.89 0.92 0.93 0.90 7.00 0.75 1.00 1.00 1.00 1.00 1.00 10.00 0.89 β 0.00 0.33 0.00 0.24 2.00 0.44 1.00 1.00 1.00 1.00 1.00 16.00 1.00 p25 p75 min max 5 5,809 47.00 5.00 95.00 35.00 99.00 25.00 (2,166) (2,300) (0.11) (0.0010) (0.0025) 171 48,386 237.00 12.00 181.00 86.30 195.00 100.00 2,231 (2,417) 4.63 0.0015 0.0062 Panel B. Fund Characteristics Fund Size ($mn) Family Size ($mn) Number of funds in family Fund Age Expense Ratio (BP) Management Fees (BP) Total Fees (BP) 12βb1 Fees (BP) Net Return (BP) Gross Return (BP) Alpha (BP) Return Gap (BP) Window Dressing (BP) Net Asset Flows 461 96,350 171.39 9.37 135.18 49.21 145.69 58.91 301 443 2.20 0.0003 0.0022 2,534 31 219168.7 21 248 158.47 126.00 7.79 8.00 61.23 130.00 88.40 67.30 64.84 144.00 34.92 50.00 2,791 999 2,828 1,168 4.51 20.42 0.0043 0.0001 0.0104 0.0011 (14) 3,297 0.08 0.40 2.00 1.00 7.00 (685.00) 8.00 2.24 (5,259) 5,242 (27.30) (0.0544) (0.0720) (0) (71) 68 (91,017) 89,887 1,026,294 628.00 87.00 280.00 145.40 293.14 100.00 6,324 6,617 55.85 0.0556 0.1120 91,278 Table 2. Expense Ratios This table presents the results from weighted least squares (WLS) estimation of Equation 1 in the paper. The dependent variable, Expense Ratio, is the ratio of the fund’s expenses divided by the value of the fund’s assets in year t (item exp_ratio in CRSP Mutual Funds). Year and ICDI investment objective (style) are included. All variables are defined in Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. (I) Unitary Board (II) (III) (IV) (V) β10.67 (8.305) Director Overlap (Fund) β26.79* (14.00) Director Overlap (Family) β34.95** (16.08) Assetβweighted Director Overlap (Fund) β23.13* (13.24) Assetβweighted Director Overlap (Family) β33.97** (14.93) Fund Age 18.04*** (4.239) 17.91*** (4.256) 17.72*** (4.231) 17.86*** (4.316) 17.70*** (4.227) Fund Size β7.210*** (1.237) β7.328*** (1.229) β7.311*** (1.225) β7.284*** (1.234) β7.311*** (1.229) Family Size β6.465*** (2.224) β5.867*** (1.926) β5.805*** (1.920) β5.808*** (1.954) β5.756*** (1.951) Board Size 19.50 (12.37) 22.08* (12.46) 22.32* (12.31) 21.46* (12.56) 21.87* (12.28) CEO is the Chairman β1.533 (6.709) 3.108 (6.828) 3.124 (6.657) 2.773 (6.945) 2.946 (6.754) Board Independence β16.04 (31.88) β13.35 (28.11) β16.02 (28.19) β11.24 (27.75) β14.36 (27.47) Constant 184.5*** (37.68) 189.0*** (38.34) 197.5*** (39.14) 184.4*** (37.75) 195.8*** (38.11) Year Fixed Effects Style Fixed Effects Family Fixed Effects r2 r2_a N Yes Yes No 0.314 0.313 38134 Yes Yes No 0.315 0.314 38134 Yes Yes No 0.316 0.315 38134 Yes Yes No 0.314 0.313 38134 Yes Yes No 0.316 0.315 38134 Table 3. Total Fees This table presents the results from weighted least squares (WLS) estimation of Equation 1 in the paper. The dependent variable is the total fund fees. Year and ICDI investment objective (style) are included. All variables are defined in Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. (I) Unitary Board (II) (III) (IV) (V) β13.56 (9.480) Director Overlap (Fund) β30.13* (15.46) Director Overlap (Family) β38.52** (17.93) Assetβweighted Director Overlap (Fund) β26.23* (14.53) Assetβweighted Director Overlap (Family) β37.06** (16.73) Fund Age 17.98*** (5.410) 17.88*** (5.449) 17.69*** (5.413) 17.83*** (5.524) 17.68*** (5.412) Fund Size β6.347*** (1.589) β6.497*** (1.578) β6.478*** (1.574) β6.446*** (1.580) β6.477*** (1.579) Family Size β7.797*** (2.549) β6.936*** (2.161) β6.854*** (2.175) β6.877*** (2.187) β6.792*** (2.202) Board Size 22.32 (14.22) 24.65* (14.59) 24.77* (14.48) 24.01 (14.71) 24.20* (14.43) CEO is the Chairman 1.061 (7.895) 6.612 (8.179) 6.576 (8.017) 6.255 (8.295) 6.355 (8.100) Board Independence β7.577 (37.28) β2.004 (32.93) β4.609 (32.84) 0.258 (32.46) β2.604 (32.09) Constant 195.4*** (40.43) 197.1*** (39.64) 205.8*** (40.71) 192.2*** (38.66) 203.7*** (39.38) Year Fixed Effects Style Fixed Effects Family Fixed Effects r2 r2_a N Yes Yes No 0.268 0.267 38134 Yes Yes No 0.268 0.267 38134 Yes Yes No 0.269 0.268 38134 Yes Yes No 0.267 0.266 38134 Yes Yes No 0.269 0.268 38134 Table 4. 12βb1 Fees This table presents the results from weighted least squares (WLS) estimation of Equation 1 in the paper. The dependent variable is the 12βb1 fees. Year and ICDI investment objective (style) are included. All variables are defined in Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. Unitary Board (I) β12.78** (5.270) Director Overlap (Fund) (II) (III) (IV) (V) β11.43 (7.943) Director Overlap (Family) β18.65* (10.10) Assetβweighted Director Overlap (Fund) β9.212 (7.120) Assetβweighted Director Overlap (Family) β17.94* (9.417) Fund Age 7.977* (4.298) 7.439* (4.373) 7.435* (4.398) 7.431* (4.372) 7.415* (4.404) Fund Size β4.294*** (1.082) β4.155*** (1.182) β4.168*** (1.172) β4.135*** (1.183) β4.158*** (1.176) Family Size β2.693 (2.264) β0.178 (2.439) β0.180 (2.437) β0.109 (2.434) β0.0876 (2.438) Board Size 6.261 (7.583) 3.138 (8.600) 4.177 (8.434) 2.707 (8.580) 3.797 (8.382) CEO is the Chairman 0.955 (5.689) 5.519 (6.239) 5.761 (6.131) 5.372 (6.295) 5.658 (6.160) Board Independence 3.993 (25.67) 23.69 (28.99) 20.47 (28.27) 25.34 (28.97) 21.77 (28.18) Constant 67.48*** (19.13) 50.32** (20.40) 56.66*** (20.14) 47.50** (19.85) 55.36*** (19.77) Year Fixed Effects Style Fixed Effects Family Fixed Effects r2 r2_a N Yes Yes No 0.0973 0.0950 24040 Yes Yes No 0.0782 0.0759 24040 Yes Yes No 0.0814 0.0790 24040 Yes Yes No 0.0774 0.0750 24040 Yes Yes No 0.0811 0.0787 24040 Table 5. Management Fees This table presents the results from weighted least squares (WLS) estimation of Equation 1 in the paper. The dependent variable, Management Fees, is the fees paid out of fund assets to the fund's investment adviser or its affiliates for managing the fund's portfolio, expressed in basis points. Year, ICDI investment objective (style), and fund family fixed effects (columns VI and VII) are included. All variables are defined in Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. Unitary Board (I) β2.263 (12.09) Director Overlap (Fund) (II) (III) (IV) (V) β17.15 (13.82) Director Overlap (Family) β6.895 (26.31) Assetβweighted Director Overlap (Fund) β2.795 (13.41) Assetβweighted Director Overlap (Family) β7.509 (23.68) Fund Age 28.19*** (8.495) 27.96*** (8.291) 28.14*** (8.499) 28.21*** (8.314) 28.12*** (8.491) Fund Size 1.922** (0.883) 1.895** (0.944) 1.900** (0.944) 1.902** (0.944) 1.901** (0.944) Family Size β4.599*** (1.635) β4.763** (2.007) β4.450** (1.831) β4.402** (2.036) β4.453** (1.860) Board Size 19.05 (16.69) 22.35 (18.86) 19.56 (16.84) 18.94 (18.87) 19.61 (17.18) CEO is the Chairman β5.685 (9.369) β3.669 (7.724) β4.732 (6.985) β4.957 (7.592) β4.715 (7.081) Board Independence β11.68 (71.97) β17.41 (58.31) β11.45 (64.26) β9.581 (58.89) β11.50 (63.44) Constant 27.19 (104.3) 39.94 (84.64) 29.42 (100.6) 25.10 (86.90) 29.91 (98.78) Year Fixed Effects Style Fixed Effects Family Fixed Effects r2 r2_a N Yes Yes No 0.183 0.182 38414 Yes Yes No 0.184 0.183 38414 Yes Yes No 0.183 0.182 38414 Yes Yes No 0.183 0.181 38414 Yes Yes No 0.183 0.182 38414 Table 6. Net Returns This table presents the results from weighted least squares (WLS) estimation of Equation 2 in the paper. The dependent variable is net return in year t, computed by compounding monthly net returns, expressed in basis points. Year and ICDI investment objective (style) are included. All variables are defined in Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. Unitary Board (I) 7.574 (34.20) Director Overlap (Fund) (II) (III) (IV) (V) 68.82 (60.90) Director Overlap (Family) 18.85 (75.16) Assetβweighted Director Overlap (Fund) 75.92 (59.08) Assetβweighted Director Overlap (Family) 20.05 (76.25) Fund Age 20.80* (12.43) 21.45* (12.58) 20.90* (12.41) 21.90* (12.65) 20.94* (12.42) Fund Size 1.630 (3.523) 1.851 (3.595) 1.708 (3.547) 1.722 (3.620) 1.710 (3.547) Family Size 12.65 (9.212) 13.58* (7.959) 12.07 (7.758) 13.88* (7.936) 12.08 (7.705) Expense Ratio β0.713*** (0.225) β0.697*** (0.226) β0.713*** (0.225) β0.695*** (0.226) β0.712*** (0.226) Board Size β9.404 (70.87) β23.57 (75.21) β10.27 (73.97) β26.19 (75.16) β10.35 (73.83) CEO is the Chairman 89.37** (35.19) 81.65** (38.24) 86.47** (38.14) 81.06** (38.09) 86.45** (37.94) Board Independence 92.52 (192.8) 118.1 (202.3) 89.53 (200.6) 121.6 (203.0) 89.44 (200.4) Constant 2162.7*** (149.3) 2105.6*** (150.0) 2159.5*** (158.3) 2100.7*** (150.9) 2158.6*** (156.9) Year Fixed Effects Style Fixed Effects Family Fixed Effects r2_a N Yes Yes No 0.866 38121 Yes Yes No 0.866 38121 Yes Yes No 0.866 38121 Yes Yes No 0.866 38121 Yes Yes No 0.866 38121 Table 7. Gross Returns This table presents the results from weighted least squares (WLS) estimation of Equation 2 in the paper. The dependent variable is the gross returns, computed by adding total fees and Net Return, expressed in basis points. Year and ICDI investment objective (style) are included. All variables are defined in Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. (I) Unitary Board (II) (III) (IV) (V) 5.067 (34.98) Director Overlap (Fund) 66.46 (61.22) Director Overlap (Family) 16.57 (75.45) Assetβweighted Director Overlap (Fund) 73.66 (59.46) Assetβweighted Director Overlap (Family) 18.22 (76.68) Fund Age 20.10 (12.25) 20.77* (12.41) 20.22* (12.25) 21.21* (12.47) 20.26* (12.26) Fund Size 2.750 (3.664) 2.951 (3.738) 2.810 (3.685) 2.826 (3.763) 2.812 (3.686) Family Size 11.54 (9.320) 12.72 (7.983) 11.24 (7.775) 13.03 (7.957) 11.25 (7.720) Expense Ratio 0.323 (0.225) 0.340 (0.227) 0.324 (0.226) 0.342 (0.227) 0.325 (0.226) Board Size β7.281 (72.63) β21.81 (77.09) β8.642 (75.85) β24.43 (77.04) β8.826 (75.70) CEO is the Chairman 92.02** (36.12) 85.05** (39.29) 89.81** (39.22) 84.44** (39.13) 89.76** (39.02) Board Independence 101.6 (196.4) 129.9 (206.1) 101.5 (204.2) 133.6 (206.8) 101.7 (204.0) Constant 2167.1*** (150.4) Yes Yes No 0.866 38121 2106.8*** (149.8) Yes Yes No 0.866 38121 2160.7*** (157.8) Yes Yes No 0.866 38121 2101.7*** (150.9) Yes Yes No 0.866 38121 2159.2*** (156.4) Yes Yes No 0.866 38121 Year Fixed Effects Style Fixed Effects Family Fixed Effects r2_a N Table 8. Alphas This table presents the results from weighted least squares (WLS) estimation of Equation 2 in the paper. The dependent variable is the fund's alpha, estimated using the FamaβFrench 4βFactor model with monthly fund returns over 2007β2009. Year and ICDI investment objective (style) are included. All variables are defined in the Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. Unitary Board (I) β0.0711 (0.229) Director Overlap (Fund) (II) (III) (IV) (V) 0.300 (0.395) Director Overlap (Family) 0.180 (0.543) Assetβweighted Director Overlap (Fund) 0.319 (0.377) Assetβweighted Director Overlap (Family) 0.155 (0.541) Fund Age 0.122 (0.0936) 0.130 (0.0926) 0.128 (0.0927) 0.132 (0.0930) 0.128 (0.0929) Fund Size 0.104*** (0.0225) 0.103*** (0.0225) 0.103*** (0.0224) 0.103*** (0.0225) 0.103*** (0.0224) Family Size 0.118** (0.0517) 0.135*** (0.0432) 0.130*** (0.0419) 0.136*** (0.0430) 0.130*** (0.0417) Board Size β0.108 (0.453) β0.206 (0.480) β0.168 (0.477) β0.215 (0.483) β0.162 (0.479) CEO is the Chairman 0.564*** (0.176) 0.551*** (0.196) 0.566*** (0.195) 0.549*** (0.195) 0.568*** (0.194) Board Independence β0.781 (1.233) β0.503 (1.235) β0.578 (1.242) β0.494 (1.230) β0.596 (1.235) Constant 4.917*** (1.524) 4.453*** (1.444) 4.574*** (1.513) 4.444*** (1.423) 4.603*** (1.502) Style Fixed Effects Family Fixed Effects r2_a N Yes No 0.444 39405 Yes No 0.444 39405 Yes No 0.444 39405 Yes No 0.444 39405 Yes No 0.444 39405 Table 9. Fees and Family Fixed Effects This table presents the results from weighted least squares (WLS) estimation of Equation 1 in the paper, incorporating family fixed effects. The dependent variable is the expense ratio, total fund fees or 12bβ1 fees. Year, ICDI investment objective (style) and fund family fixed effects are included. All variables are defined in Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. Director Overlap (Fund) Expense Ratios β2.495 (13.63) Assetβweighted Director Overlap (Fund) Total Fees β6.100 (15.50) β0.646 (13.95) 12bβ1 Fees 10.81** (4.912) β4.172 (15.87) Management Fees β33.89* (19.45) 10.45*** (3.568) 11.68 (22.20) Fund Age 15.03*** (3.883) 15.03*** (3.901) 14.52*** (5.013) 14.50*** (5.042) 6.938 (4.692) 6.966 (4.710) 25.64*** (8.226) 25.71*** (8.060) Fund Size β6.826*** (1.138) β6.824*** (1.136) β5.705*** (1.547) β5.697*** (1.542) β4.207*** (1.139) β4.218*** (1.140) 2.949*** (1.027) 2.949*** (1.059) Family Size 4.537* (2.554) 4.524* (2.549) 3.741 (2.766) 3.711 (2.763) . . . . 0.662 (7.904) 0.464 (7.926) Board Size 43.58*** (10.68) 43.47*** (11.23) 45.51*** (13.61) 45.66*** (14.31) 6.527** (3.036) 5.732* (3.073) 102.6*** (26.65) 97.53*** (29.34) CEO is the Chairman β36.02*** (12.83) β36.65*** (13.11) β31.13** (15.05) β31.80** (15.34) β9.751* (5.665) β9.518 (5.916) β73.33*** (21.87) β88.78*** (27.93) Board Independence 60.32** (26.36) 60.61** (25.45) 61.27* (34.69) 60.82* (33.56) 0.173 (15.05) 1.914 (14.77) 105.7 (103.7) 119.0 (121.0) Constant β44.29 (50.10) β45.56 (48.21) β29.77 (59.40) β31.00 (57.28) 47.12*** (13.12) 48.01*** (12.67) β277.0*** (79.18) β309.0*** (95.45) Year Fixed Effects Style Fixed Effects Family Fixed Effects r2 r2_a N Yes Yes Yes 0.403 0.397 38134 Yes Yes Yes 0.403 0.397 38134 Yes Yes Yes 0.370 0.363 38134 Yes Yes Yes 0.370 0.363 38134 Yes Yes Yes 0.194 0.184 24040 Yes Yes Yes 0.194 0.184 24040 Yes Yes Yes 0.298 0.291 38414 Yes Yes Yes 0.297 0.290 38414 Table 10. Fund Performance with Family Fixed Effects This table presents the results from weighted least squares (WLS) estimation of Equation 2 in the paper. The dependent variable is net return, gross return or alpha in year t. Year and ICDI investment objective (style) and family fixed effects are included. All variables are defined in Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. Director Overlap (Fund) Net Returns 138.1** (66.42) Assetβweighted Director Overlap (Fund) Gross Returns 134.5** (67.44) 124.9** (55.55) Alphas 0.109 (0.487) 121.4** (56.32) 0.228 (0.444) Fund Age 19.23 (12.48) 19.68 (12.53) 18.34 (12.35) 18.78 (12.37) 0.120 (0.0904) 0.121 (0.0906) Fund Size 0.954 (3.227) 0.728 (3.227) 2.242 (3.348) 2.022 (3.346) 0.0968*** 0.0965*** (0.0210) (0.0209) Family Size β307.9** (128.9) β307.2** (129.0) β308.8** (128.8) β308.1** (128.9) β0.181 (0.597) β0.181 (0.598) Expense Ratio β0.904*** (0.212) β0.905*** (0.210) 0.120 (0.210) 0.120 (0.208) Board Size 161.9*** (52.83) 153.3*** (51.73) 162.7*** (52.75) 154.4*** (51.66) 0.790* (0.433) 0.761* (0.435) CEO is the Chairman 167.0 (102.8) 171.9* (101.3) 172.8* (102.4) 177.7* (100.7) 0.941*** (0.359) 0.899*** (0.334) Board Independence β185.2 (198.3) β161.4 (189.3) β185.7 (199.6) β162.6 (190.5) β1.919 (1.571) β1.844 (1.513) Constant 5535.1*** 5541.0*** 5550.7*** 5556.7*** 7.073 (1480.9) (1478.7) (1478.2) (1475.9) (7.323) 6.988 (7.312) Year Fixed Effects Style Fixed Effects Family Fixed Effects r2_a N Yes Yes Yes 0.866 38121 Yes Yes Yes 0.460 39405 Fund Return β1 Yes Yes Yes 0.866 38121 Yes Yes Yes 0.866 38121 Yes Yes Yes 0.866 38121 Yes Yes Yes 0.460 39405 Table 11. Managerial Skill and Window Dressing This table presents the results from weighted least squares (WLS) estimation of Equation 2 in the paper. In Columns I and II, the dependent variable is the fund's return gap, calculated using the procedure developed by KSZ . In Columns III and IV, the dependent variable is the backward holdings return gap developed by AGL. Year, ICDI investment objective (style), and fund family fixed effects are included. All variables are defined in the Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. Managerial Skill (I) Director Overlap (Fund) (II) 16.73 (13.43) Assetβweighted Director Overlap (Fund) Window Dressing (III) 54.75** (27.58) 19.17 (13.71) (IV) 0.600 (22.96) Fund Age β1.057 (1.042) β0.942 (1.035) 15.61*** (2.844) 15.68*** (2.842) Fund Size 0.181 (0.705) 0.104 (0.688) β8.444*** (1.765) β8.487*** (1.796) Family Size 1.136 (2.983) 1.316 (2.950) 14.66*** (5.495) 14.98*** (5.517) Board Size 3.046 (9.079) 2.132 (9.160) β15.64 (19.16) β7.052 (17.22) CEO is the Chairman β13.33 (10.14) β16.25 (11.28) β38.46* (21.91) β8.021 (21.78) Board Independence 33.91 (26.02) 39.34 (27.48) β300.1*** (74.17) β299.8*** (69.57) Constant β50.38 (47.59) β55.00 (47.54) 51.93 (100.5) 64.38 (90.02) Style Fixed Effects Year Fixed Effects Family Fixed Effects r2_a N Yes Yes Yes 0.0771 6622 Yes Yes Yes 0.0777 6622 Yes Yes Yes 0.183 7215 Yes Yes Yes 0.181 7215 Table 12. Strategic Performance Transfer (I) Same Family (II) (III) 49.66* (27.90) Director Overlap Measures (Director Overlap of High Fee fund >= Director Overlap of Low Fee Fund) * Same Family 59.20** (28.56) (Director Overlap of Low Fee fund > Director Overlap of High Fee Fund) * Same Family β7.576 (22.04) Assetβweighted Director Overlap Measures (Director Overlap of HIgh Fee fund >= Director Overlap of Low Fee Fund) * Same Family 57.78** (28.52) (Director Overlap of Low Fee fund > Director Overlap of High Fee Fund) * Same Family 0.520 (25.55) Size of the highβfee fund 10.54** (4.619) 10.77** (4.588) 10.70** (4.589) Size of the lowβfee fund β7.777*** (2.803) β7.678*** (2.737) β7.638*** (2.741) Age of the highβfee fund 44.73** (21.86) 48.77** (20.65) 48.07** (20.80) Age of the lowβfee fund β12.46 (13.98) β13.13 (14.59) β12.76 (14.58) β28.76 (17.86) β33.68* (17.21) β32.89* (17.34) Constant 30.11 (64.42) 28.25 (59.82) 28.04 (60.70) Year Fixed Effects Style Fixed Effects Family Fixed Effects r2 r2_a N Yes Yes No 0.0172 0.0168 749471 Yes Yes No 0.0175 0.0171 749471 Yes Yes No 0.0174 0.0170 749471 Same style Table 13. Net Asset Flows This table presents the results from weighted least squares (WLS) estimation of Equation 2 in the paper. The dependent variable is the fund's net asset flows, calculates as TNA_flow = mtna β (mtna[_nβ1]*(1+mret)) . Year, ICDI investment objective (style), and fund family fixed effects (columns VI and VII) are included. All variables are defined in the Appendix Table. Standard errors are adjusted for heteroskedasticity and correlation across observations belonging to the same fund family, and are presented in parantheses. * , ** and *** indicate significance at the 10%, 5% and 1% level, respectively. Unitary Board (I) β111.9 (125.3) Director Overlap (Fund) (II) (III) (IV) (V) 349.1 (257.8) Director Overlap (Family) (VI) (VII) 1063.7* (603.6) 159.6 (215.3) Assetβweighted Director Overlap (Fund) 426.1 (273.1) Assetβweighted Director Overlap (Family) 1081.8* (591.9) 185.8 (199.2) Fund Age 633.6** (272.3) 637.8** (273.7) 636.4** (273.4) 640.4** (274.4) 636.8** (273.3) 651.9** (272.9) 655.7** (274.6) Fund Size β1 266.9*** (87.52) 267.0*** (87.50) 266.6*** (87.44) 266.3*** (87.06) 266.6*** (87.40) 300.3*** (95.80) 298.3*** (94.84) Family Sizeβ1 β158.7** (76.96) β134.9* (70.25) β141.1* (72.36) β132.4* (71.98) β140.8* (73.15) β27.74 (93.32) β26.35 (93.41) Expense Ratio β1 β2.645 (1.691) β2.473 (1.702) β2.526 (1.715) β2.456 (1.713) β2.521 (1.723) β3.133* (1.604) β3.134* (1.598) Fund Return β1 0.00298 (0.0133) 0.00300 (0.0134) 0.00324 (0.0133) 0.00240 (0.0136) 0.00319 (0.0133) 0.00608 (0.0131) 0.00513 (0.0133) Board Size 329.8* (191.4) 210.9 (188.8) 262.3 (185.9) 189.1 (199.8) 259.1 (188.3) β575.0 (609.3) β661.4 (638.8) CEO is the Chairman β104.4 (134.6) β116.6 (119.1) β96.20 (130.4) β122.5 (121.6) β97.30 (132.2) β424.1 (410.3) β440.7 (428.0) Board Independence β1516.6* (820.6) β1149.8 (706.1) β1261.7* (749.6) β1107.8 (711.7) β1254.7* (750.5) β763.4 (1144.2) β521.5 (1121.2) Constant β226.0 (761.4) β866.1 (759.7) β658.5 (778.8) β939.2 (792.3) β683.4 (787.3) β1415.5 (1485.2) β1417.9 (1496.2) Style Fixed Effects Family Fixed Effects r2_a N Yes No 0.0519 36146 Yes No 0.0519 36146 Yes No 0.0518 36146 Yes No 0.0520 36146 Yes No 0.0518 36146 Yes Yes 0.0487 36146 Yes Yes 0.0489 36146
